The invention described herein may be manufactured by or for the Government of the United States of America for Governmental purposes without the payment of any royalties thereon or therefor.
(1) Field of the Invention
The invention relates generally to the field of estimation and tracking, and more particularly to systems and methods for bearings-only contact state estimation and target motion analysis for marine applications.
(2) Description of the Prior Art
In the ocean environment, localization and tracking of an acoustic contact from sonar measurements are of considerable interest. The two-dimensional contact state estimation, or target motion analysis, problem captures the fundamental essentials of tracking. Here a moving observer (xe2x80x9cownshipxe2x80x9d) monitors sonar bearings from an acoustic contact (xe2x80x9ctargetxe2x80x9d) assumed to have constant velocity, one processes those measurements to estimate contact location and velocity.
A fundamental property of a bearings-only target motion analysis is that the process is not completely observable for any single leg of ownship motion. This is clear from the fact that several target trajectories will generate the same bearing-measurement history for a constant velocity observer. The range to the target becomes observable only following a maneuver by the observer. Several estimation techniques have been applied to the bearings-only target motion analysis, with varying results. The differences in methods involve the modeling of the process and the selection of the estimation algorithm. The extended Kalman filter (xe2x80x9cEKFxe2x80x9d) in a Cartesian state-space exhibits divergence problems which yield poor estimates with optimistic uncertainties. The pseudo-linear estimation technique is known to produce biased solutions with optimistic covariances; depending on the scenario geometry, the bias can be severe. The maximum likelihood estimator (xe2x80x9cMLExe2x80x9d) is one of the present techniques of choice, but it is sensitive to the initialization. A two-stage hierarchical estimation approach has been proposed, but this and the other methods are based on linear filtering and estimation techniques and are approximations to the complex nonlinear nature of the real-world problem.
It is therefore an object of the invention to provide a new and improved system and method for bearings-only contact state estimation and target motion analysis for marine applications.
In brief summary, in one aspect the invention provides a system for bearings-only contact state estimation in response to target bearing and ownship speed and course (i.e., velocity) information provided for a plurality of observation legs at successive points in time, including a plurality of neural networks and a data fusion circuit. Each of the neural networks generates range-normalized parameter estimate information for one of the observation legs in response to target bearing and ownship course information for an associated one of the observation legs, provided thereto at each point in time and information generated for the previous point in time. The data fusion circuit receives the range-normalized parameter estimate information from the neural networks and generates the contact state estimation in response thereto.
In a further aspect, the invention provides a neural network neural networks for generating range-normalized parameter estimate information for one of the observation legs in response to target bearing and ownship speed and course information for an associated one of the observation legs, provided thereto at each point in time and information generated for the previous point in time. The neural network includes an input layer, a hidden layer and an output layer. The input layer comprises a plurality of input nodes, at least some of the input nodes receiving the bearing information and the ownship speed and course information for the respective one of the observation legs, at least others of the input nodes receiving the delayed intermediate network state information. The hidden layer comprises a plurality of hidden nodes, for receiving the bearing information, the ownship speed and course information and the delayed intermediate network state information from the input nodes and processing it in response to a weight information associated with each input node and respective hidden node in relation to a predetermined non-linear function to generate intermediate network state information. The intermediate network state information generated at each point in time comprises the delayed intermediate network state information for a subsequent point in time. The output layer comprises a plurality of output nodes for generating the range-normalized parameter estimate information in relation to the contact state information generated by the hidden layer at each point in time.